Speakers

Kevin Leyton-Brown is a professor of Computer Science and a Distinguished University Scholar at the University of British Columbia. He holds a Canada CIFAR AI Chair at the Alberta Machine Intelligence Institute and is an associate member of the Vancouver School of Economics. He received a PhD and an M.Sc. from Stanford University (2003; 2001) and a B.Sc. from McMaster University (1998). He studies artificial intelligence, mostly at the intersection of machine learning with either the design and operation of electronic markets or the design of heuristic algorithms. He has helped to design a government auction that reallocated North American radio spectrum; an electronic market that linked Ugandan farmers with buyers for surplus crops; and widely used open source software such as SATzilla (an algorithm portfolio for solving satisfiability problems), Mechanical TA (peer grading software used at universities around the world), and AutoWEKA (a machine learning tool that both selects a model family and optimizes its hyperparameters). He is increasingly interested in large language models, particularly as components of agent architectures. He believes we have both a moral obligation and a historical opportunity to leverage AI to benefit underserved communities, particularly in the developing world.

Leyton-Brown has co-written over 175 peer-refereed technical articles; his work has received over 30,000 citations and an h-index of 68. He is a Fellow of the Royal Society of Canada (RSC; awarded in 2023), the Association for Computing Machinery (ACM; awarded in 2020), and the Association for the Advancement of Artificial Intelligence (AAAI; awarded in 2018). He was a member of a team that won a 2024 Technology & Engineering Emmy Award and the 2018 INFORMS Franz Edelman Award for Achievement in Advanced Analytics, Operations Research and Management Science, described as "the leading O.R. and analytics award in the industry." Leyton-Brown also received UBC's 2015 Charles A. McDowell Award for Excellence in Research, a 2014 NSERC E.W.R. Steacie Memorial Fellowship—previously given to a computer scientist only 10 times since its establishment in 1965—and a 2013 Outstanding Young Computer Science Researcher Prize from the Canadian Association of Computer Science. He and his coauthors have received paper awards from AIJ, JAIR, ACM-EC, KDD, AAMAS and LION, and numerous medals at international SAT solver competitions .

Leyton-Brown has coauthored two popular textbooks, co-taught two Coursera courses on "Game Theory" to over a million students (and counting!), and received awards for his teaching at UBC, including a Killam Teaching Prize. He served as General Chair of the 2023 ACM Conference on Economics and Computation (ACM-EC); Program Co-Chair for AAAI 2021 (one of the top two international conferences on artificial intelligence); and Program Chair for ACM-EC 2012. He has also served as Chair of the ACM Special Interest Group on Economics and Computation and Associate Editor for the Artificial Intelligence Journal (AIJ), the Journal of Artificial Intelligence Research (JAIR), ACM Transactions on Economics and Computation (ACM-TEAC), and AI Access.

He has held a wide range of visiting professor/researcher positions, at the Simons Institute for the Theory of Computing at UC Berkeley (Apr–May 2022; Aug–Sep, Nov 2016; Sep–Dec 2015); Technion Israel Institute of Technology (April 2018); Microsoft Research New York City (Jan–Feb 2018); Microsoft Research New England (Mar–Jun 2016); Harvard's EconCS group (Mar–Jun 2016); the Institute for Advanced Studies at Hebrew University of Jerusalem, Israel (Mar–Jun 2011); and Makerere University in Kampala, Uganda (Sep 2010–Jan 2011).

Leyton-Brown currently advises Auctionomics, AI21, OneChronos and AnyLog. He is a co-founder of Kudu.ug and Meta-Algorithmic Technologies. He was scientific advisor to UBC spinoff Zite until it was acquired by CNN in 2011. His past consulting has included work for Zynga, Qudos, Trading Dynamics, Ariba, and Cariocas.

Sheila McIlraith is a Professor in the Department of Computer Science, University of Toronto, a CIFAR AI Chair (Vector Institute), and an Associate Director and Research Lead of the Schwartz Reisman Institute for Technology and Society. McIlraith's research is in the areas of AI knowledge representation, automated reasoning and machine learning. Her research focuses on AI sequential decision making, broadly construed, through the lens of human-compatible AI. McIlraith is a fellow of the ACM, a fellow of AAAI, and a Schmidt Sciences AI2050 Senior Fellow. McIlraith is a member of the Canadian AI Safety Institute (CAISI) Research Council and is currently serving as Chair of the Standing Committee of the One Hundred Year Study on Artificial Intelligence (AI100). McIlraith has served on the editorial boards of AIJ, JAIR, and Artificial Intelligence Magazine. She has also served as program co-chair of AAAI2018, KR2012, and ISWC2004, as well as conference co-chair of ICAPS2024. McIlraith and co-authors have been honoured with a number of paper recognitions, including three test-of-time style awards. She has also been honoured with a CAIAC Lifetime Achievement Award for research excellence in AI. McIlraith initiated and co-leads the University of Toronto Embedded Ethics Education Initiative (E3I) with annual student enrollment in E3I programming nearing 10,000.